Abstract
Abstract. Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud–Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.
Highlights
Industrial, residential, transportation, and agricultural activities have considerably increased the amount of aerosols in the atmosphere since the onset of the Industrial Revolution in the mid-19th century (e.g., Solomon et al, 2007)
While reduced emissions and a lowered cap of relative humidity for sulfate hygroscopic growth yield a reduction in aerosol optical depth (AOD) in CM3, internal mixing of black carbon and sulfate introduced in CM3 produces a higher aerosol absorption optical depth (AAOD) than CM2.1, as explained by Persad et al (2014)
Donner et al (2011) evaluated basic aerosol-related properties of CM2.1 vs. CM3, leading to the general conclusion that the direct effects of aerosols are more realistically simulated in CM3
Summary
Industrial, residential, transportation, and agricultural activities have considerably increased the amount of aerosols in the atmosphere since the onset of the Industrial Revolution in the mid-19th century (e.g., Solomon et al, 2007). In order to fully understand how aerosols influence climate, it becomes necessary to employ numerical models to simulate aerosol distributions and properties, evaluate their perturbations to the radiative budget, and investigate changes in thermal, hydrological, and dynamical atmospheric and oceanic properties. Because the horizontal and vertical distributions of anthropogenic scattering and absorbing aerosols dominate a suite of climate responses to the forcings (Ginoux et al, 2006; Donner et al, 2011; Naik et al, 2013; Ocko et al, 2014), it is critical to improve model performance of aerosol optical properties. We show that comparing multiple modelsimulated aerosol properties – from two prominent, related climate models with vastly different aerosol treatments – to available datasets from spatially collocated ground-based and satellite instruments is important for determining model biases. We select seven locations worldwide that represent a diversity of conditions and use highresolution point data (AERONET) and three-dimensional satellite data (CALIOP) to better understand the model biases
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